【摘要】：近年來,由于經(jīng)濟的快速發(fā)展和計算機科技的普遍應(yīng)用,應(yīng)用在戶外的監(jiān)控系統(tǒng)對圖像處理技術(shù)的要求也越來越高。但是環(huán)境問題的日益突出給這些技術(shù)的應(yīng)用帶來了挑戰(zhàn),尤其是當(dāng)前嚴(yán)重的霧、霾等惡劣天氣。惡劣的天氣不僅會影響人們的日常生活,給生活帶來不便,并且使獲得的圖像的質(zhì)量變低,最終成像效果變差。嚴(yán)重時更可能使某些戶外的監(jiān)控系統(tǒng)無法正常運行,而且在安全方面存在很大隱患,尤其是交通方面。是以,對霧霾天氣下所拍攝的圖像進行圖像增強處理無論是在日常生活還是專門部門都變得非常重要而且意義重大。本文主要的研究工作如下:(1)從圖像增強的理論基礎(chǔ)、數(shù)字圖像的表示、獲取方法、處理過程和各種圖形類型的基本特點等基礎(chǔ)概念入手,綜合比較了兩種局部化增強圖像方法,基于局部對比度方法和基于局部方差法。并提出了在小波域的基礎(chǔ)上做改進的Retinex算法,通過與直方圖均衡化的去霧效果做實驗比較可得,改進的算法有著良好的去霧效果,且各種客觀指標(biāo)也比較高。(2)在頻域變換的理論基礎(chǔ)上,分析并使用Sym系列小波變換的圖像處理增強方法,深入研究了小波變換技術(shù)在圖像加強方面的方法和應(yīng)用,闡述了小波分解時選取合適的小波基的重要性,以及分解后獲得的不同高低頻信息采取基于各自特點差別的處理機制,會使最終效果有很大不同,以此來使圖像的清晰度得到改善。將該方法的去霧效果與同態(tài)濾波算法去霧做了比較,實驗證明本文方法去霧效果更好。最后還將該方法運用到了交通車輛監(jiān)控系統(tǒng)中,其處理效果也很好。
[Abstract]:In recent years, with the rapid development of economy and the widespread application of computer science and technology, the requirement of image processing technology for outdoor surveillance system is more and more high. However, the increasingly prominent environmental problems have brought challenges to the application of these technologies, especially the current severe fog, haze and other bad weather. The bad weather will not only affect people's daily life, bring inconvenience to life, but also make the quality of the image become lower, and the final imaging effect will become worse. It is more likely that some outdoor monitoring systems will not work properly when it is serious, and there are great hidden dangers in safety, especially in traffic. Therefore, image enhancement processing of images taken in haze weather has become very important and significant both in daily life and in specialized departments. The main work of this paper is as follows: (1) starting with the basic concepts of image enhancement, such as image enhancement theory, digital image representation, acquisition method, processing process and the basic characteristics of various graphic types, two localization enhancement methods are comprehensively compared. Based on local contrast method and local variance method. An improved Retinex algorithm based on wavelet domain is proposed. Compared with the experimental results of histogram equalization, the improved algorithm has a good de-fogging effect. And various objective indexes are also relatively high. (2) based on the theory of frequency domain transform, the image processing enhancement method of Sym series wavelet transform is analyzed and used, and the method and application of wavelet transform technology in image enhancement are deeply studied. The importance of selecting suitable wavelet bases in wavelet decomposition is expounded, and the processing mechanism based on the characteristics and differences of the different high and low frequency information obtained by wavelet decomposition will make the final effect very different. In order to improve the clarity of the image. Compared with the homomorphic filtering algorithm, the effect of the proposed method is better than that of the homomorphic filtering algorithm. Finally, the method is applied to the traffic vehicle monitoring system, and its processing effect is very good.
【學(xué)位授予單位】：山東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.41

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本文編號：2221123